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README.md

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 This repository focuses on building foundational visual models for large language models (LLMs) using large-scale datasets such as LAION400M and COYO700M. We employ sample-to-cluster contrastive learning to optimize performance. Our models are primarily used for multimodal visual large language models, such as LLaVA.  
 
-We adopted the official [LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT) and the official training dataset([LLaVA-NeXT-Data](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Data)) for evaluating the foundational visual models .  
+We adopted the official [LLaVA-NeXT](https://github.com/LLaVA-VL/LLaVA-NeXT) and the official training dataset [LLaVA-NeXT-Data](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Data) for evaluating the foundational visual models.  
 
 
 | Vision Tower             | RoPE2D | ChartQA | DocVQA | InfoVQA | OCRBench | MMMU  |